Reporte Data Churn

Dataset statistics

Number of variables	25
Number of observations	8440
Missing cells	94755
Missing cells (%)	44.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	6.4 MiB
Average record size in memory	791.3 B

Variable types

Categorical	12
Numeric	10
Unsupported	3

Alerts

`ClaseVehiculo__c` has constant value "99999"	Constant
`TipoVehiculo__c` has constant value "99999"	Constant
`churn` is highly correlated with `n_prod_prev` and 3 other fields	High correlation
`n_prod_prev` is highly correlated with `churn` and 3 other fields	High correlation
`total_siniestros` is highly correlated with `churn` and 3 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `churn` and 3 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `churn` and 3 other fields	High correlation
`Activos__c` is highly correlated with `AnnualRevenue` and 1 other fields	High correlation
`AnnualRevenue` is highly correlated with `Activos__c` and 1 other fields	High correlation
`EgresosAnuales__c` is highly correlated with `Activos__c` and 1 other fields	High correlation
`churn` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`n_prod_prev` is highly correlated with `churn` and 2 other fields	High correlation
`total_siniestros` is highly correlated with `churn` and 2 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `churn` and 2 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `AnnualRevenue` and 1 other fields	High correlation
`Activos__c` is highly correlated with `AnnualRevenue` and 1 other fields	High correlation
`AnnualRevenue` is highly correlated with `anios_ultimo_siniestro` and 2 other fields	High correlation
`EgresosAnuales__c` is highly correlated with `anios_ultimo_siniestro` and 2 other fields	High correlation
`churn` is highly correlated with `n_prod_prev` and 3 other fields	High correlation
`n_prod_prev` is highly correlated with `churn` and 3 other fields	High correlation
`total_siniestros` is highly correlated with `churn` and 3 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `churn` and 3 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `churn` and 3 other fields	High correlation
`AnnualRevenue` is highly correlated with `EgresosAnuales__c`	High correlation
`EgresosAnuales__c` is highly correlated with `AnnualRevenue`	High correlation
`CodigoTipoAsegurado__c` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`PuntoVenta__c` is highly correlated with `tipo_ramo_name` and 4 other fields	High correlation
`tipo_ramo_name` is highly correlated with `PuntoVenta__c` and 5 other fields	High correlation
`tipo_prod_desc` is highly correlated with `tipo_ramo_name` and 3 other fields	High correlation
`NumeroPoliza__c` is highly correlated with `PuntoVenta__c` and 5 other fields	High correlation
`FechaInicioVigencia__ctrim` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`churn` is highly correlated with `n_prod_prev` and 2 other fields	High correlation
`n_prod_prev` is highly correlated with `CodigoTipoAsegurado__c` and 8 other fields	High correlation
`total_siniestros` is highly correlated with `CodigoTipoAsegurado__c` and 7 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `CodigoTipoAsegurado__c` and 9 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `n_prod_prev` and 3 other fields	High correlation
`Activos__c` is highly correlated with `anios_ultimo_siniestro` and 4 other fields	High correlation
`AnnualRevenue` is highly correlated with `anios_ultimo_siniestro` and 3 other fields	High correlation
`MontoAnual__c` is highly correlated with `FechaInicioVigencia__ctrim` and 3 other fields	High correlation
`OtrosIngresos__c` is highly correlated with `Activos__c` and 2 other fields	High correlation
`EgresosAnuales__c` is highly correlated with `anios_ultimo_siniestro` and 3 other fields	High correlation
`EstadoCivil__pc` is highly correlated with `Genero__pc`	High correlation
`Genero__pc` is highly correlated with `MontoAnual__c` and 1 other fields	High correlation
`ciudad_name` is highly correlated with `total_pagado_smmlv`	High correlation
`edad` is highly correlated with `MontoAnual__c`	High correlation
`MarcaVehiculo__c` has 8440 (100.0%) missing values	Missing
`MdeloVehiculo__c` has 8440 (100.0%) missing values	Missing
`n_prod_prev` has 6743 (79.9%) missing values	Missing
`total_siniestros` has 6581 (78.0%) missing values	Missing
`total_pagado_smmlv` has 6581 (78.0%) missing values	Missing
`anios_ultimo_siniestro` has 6581 (78.0%) missing values	Missing
`Activos__c` has 4282 (50.7%) missing values	Missing
`AnnualRevenue` has 4282 (50.7%) missing values	Missing
`MontoAnual__c` has 8433 (99.9%) missing values	Missing
`OtrosIngresos__c` has 5105 (60.5%) missing values	Missing
`Profesion__pc` has 8440 (100.0%) missing values	Missing
`EgresosAnuales__c` has 4282 (50.7%) missing values	Missing
`EstadoCivil__pc` has 4141 (49.1%) missing values	Missing
`Genero__pc` has 4141 (49.1%) missing values	Missing
`ciudad_name` has 4141 (49.1%) missing values	Missing
`edad` has 4142 (49.1%) missing values	Missing
`OtrosIngresos__c` is highly skewed (γ1 = 51.4657287)	Skewed
`MarcaVehiculo__c` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`MdeloVehiculo__c` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Profesion__pc` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`total_pagado_smmlv` has 194 (2.3%) zeros	Zeros
`OtrosIngresos__c` has 3168 (37.5%) zeros	Zeros

Reproduction

Analysis started	2022-06-04 05:31:45.493506
Analysis finished	2022-06-04 05:33:02.439508
Duration	1 minute and 16.95 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

CodigoTipoAsegurado__c
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	478.2 KiB

1	8040
4	291
3	58
2	51

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	8440
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	4

Common Values

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

Most occurring characters

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	8440	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	8440	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8440	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	8040	95.3%
4	291	3.4%
3	58	0.7%
2	51	0.6%

PuntoVenta__c
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	175
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3388.13519

Minimum	5
Maximum	20001
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	5
5-th percentile	103
Q1	1000
median	2466
Q3	3502
95-th percentile	9721
Maximum	20001
Range	19996
Interquartile range (IQR)	2502

Descriptive statistics

Standard deviation	3360.801403
Coefficient of variation (CV)	0.9919324982
Kurtosis	-0.1232953451
Mean	3388.13519
Median Absolute Deviation (MAD)	1464
Skewness	1.078266357
Sum	28595861
Variance	11294986.07
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3301	1007	11.9%
9721	977	11.6%
404	400	4.7%
1048	396	4.7%
1503	375	4.4%
103	339	4.0%
1002	311	3.7%
3502	302	3.6%
301	268	3.2%
1203	198	2.3%
Other values (165)	3867	45.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5	127	1.5%
8	3	< 0.1%
9	5	0.1%
14	30	0.4%
16	38	0.5%
23	75	0.9%
25	38	0.5%
26	49	0.6%
102	5	0.1%
103	339	4.0%

Value	Count	Frequency (%)
20001	6	0.1%
10111	6	0.1%
9977	6	0.1%
9971	1	< 0.1%
9943	3	< 0.1%
9820	2	< 0.1%
9723	4	< 0.1%
9721	977	11.6%
9715	17	0.2%
9706	2	< 0.1%

tipo_ramo_name
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	596.6 KiB

automoviles	4754
responsabilidad civil	3686

Length

Max length	21
Median length	11
Mean length	15.36729858
Min length	11

Characters and Unicode

Total characters	129700
Distinct characters	17
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	responsabilidad civil
2nd row	automoviles
3rd row	automoviles
4th row	automoviles
5th row	responsabilidad civil

Common Values

Value	Count	Frequency (%)
automoviles	4754	56.3%
responsabilidad civil	3686	43.7%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
automoviles	4754	39.2%
responsabilidad	3686	30.4%
civil	3686	30.4%

Most occurring characters

Value	Count	Frequency (%)
i	19498	15.0%
o	13194	10.2%
a	12126	9.3%
s	12126	9.3%
l	12126	9.3%
e	8440	6.5%
v	8440	6.5%
d	7372	5.7%
m	4754	3.7%
u	4754	3.7%
Other values (7)	26870	20.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	126014	97.2%
Space Separator	3686	2.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	19498	15.5%
o	13194	10.5%
a	12126	9.6%
s	12126	9.6%
l	12126	9.6%
e	8440	6.7%
v	8440	6.7%
d	7372	5.9%
m	4754	3.8%
u	4754	3.8%
Other values (6)	23184	18.4%

Space Separator

Value	Count	Frequency (%)
	3686	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	126014	97.2%
Common	3686	2.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	19498	15.5%
o	13194	10.5%
a	12126	9.6%
s	12126	9.6%
l	12126	9.6%
e	8440	6.7%
v	8440	6.7%
d	7372	5.9%
m	4754	3.8%
u	4754	3.8%
Other values (6)	23184	18.4%

Common

Value	Count	Frequency (%)
	3686	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	129700	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	19498	15.0%
o	13194	10.2%
a	12126	9.3%
s	12126	9.3%
l	12126	9.3%
e	8440	6.5%
v	8440	6.5%
d	7372	5.7%
m	4754	3.7%
u	4754	3.7%
Other values (7)	26870	20.7%

tipo_prod_desc
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	582.6 KiB

automoviles	4596
extracontractual	2602
profesionales medicos	697
operadores portuarios	362
otras	183

Length

Max length	21
Median length	11
Mean length	13.66611374
Min length	5

Characters and Unicode

Total characters	115342
Distinct characters	18
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	extracontractual
2nd row	automoviles
3rd row	automoviles
4th row	automoviles
5th row	extracontractual

Common Values

Value	Count	Frequency (%)
automoviles	4596	54.5%
extracontractual	2602	30.8%
profesionales medicos	697	8.3%
operadores portuarios	362	4.3%
otras	183	2.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
automoviles	4596	48.4%
extracontractual	2602	27.4%
profesionales	697	7.3%
medicos	697	7.3%
operadores	362	3.8%
portuarios	362	3.8%
otras	183	1.9%

Most occurring characters

Value	Count	Frequency (%)
o	15516	13.5%
a	14006	12.1%
t	12947	11.2%
e	10013	8.7%
l	7895	6.8%
s	7594	6.6%
u	7560	6.6%
r	7532	6.5%
i	6352	5.5%
c	5901	5.1%
Other values (8)	20026	17.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	114283	99.1%
Space Separator	1059	0.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	15516	13.6%
a	14006	12.3%
t	12947	11.3%
e	10013	8.8%
l	7895	6.9%
s	7594	6.6%
u	7560	6.6%
r	7532	6.6%
i	6352	5.6%
c	5901	5.2%
Other values (7)	18967	16.6%

Space Separator

Value	Count	Frequency (%)
	1059	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	114283	99.1%
Common	1059	0.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	15516	13.6%
a	14006	12.3%
t	12947	11.3%
e	10013	8.8%
l	7895	6.9%
s	7594	6.6%
u	7560	6.6%
r	7532	6.6%
i	6352	5.6%
c	5901	5.2%
Other values (7)	18967	16.6%

Common

Value	Count	Frequency (%)
	1059	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	115342	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	15516	13.5%
a	14006	12.1%
t	12947	11.2%
e	10013	8.7%
l	7895	6.8%
s	7594	6.6%
u	7560	6.6%
r	7532	6.5%
i	6352	5.5%
c	5901	5.1%
Other values (8)	20026	17.4%

ClaseVehiculo__c
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	511.1 KiB

99999	8440

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	42200
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	8440	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
99999	8440	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	42200	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	42200	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	42200	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	42200	100.0%

MarcaVehiculo__c
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	8440
Missing (%)	100.0%
Memory size	66.1 KiB

MdeloVehiculo__c
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	8440
Missing (%)	100.0%
Memory size	66.1 KiB

TipoVehiculo__c
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	511.1 KiB

99999	8440

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	42200
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	8440	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
99999	8440	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	42200	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	42200	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	42200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	42200	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	42200	100.0%

NumeroPoliza__c
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	8040
Distinct (%)	95.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2201742.428

Minimum	1000002
Maximum	3173059
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	1000002
5-th percentile	1002345.7
Q1	1009391.75
median	3007879.5
Q3	3068286.5
95-th percentile	3166538.05
Maximum	3173059
Range	2173057
Interquartile range (IQR)	2058894.75

Descriptive statistics

Standard deviation	1015038.799
Coefficient of variation (CV)	0.4610161414
Kurtosis	-1.892128615
Mean	2201742.428
Median Absolute Deviation (MAD)	157102.5
Skewness	-0.3157750033
Sum	1.858270609 × 10¹⁰
Variance	1.030303763 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1006109	3	< 0.1%
1004747	3	< 0.1%
1005696	3	< 0.1%
1007149	3	< 0.1%
1006106	3	< 0.1%
1007164	3	< 0.1%
1004295	3	< 0.1%
1004267	3	< 0.1%
1007148	3	< 0.1%
3007896	3	< 0.1%
Other values (8030)	8410	99.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1000002	1	< 0.1%
1000004	1	< 0.1%
1000006	1	< 0.1%
1000009	1	< 0.1%
1000010	1	< 0.1%
1000014	1	< 0.1%
1000016	1	< 0.1%
1000017	1	< 0.1%
1000020	1	< 0.1%
1000022	1	< 0.1%

Value	Count	Frequency (%)
3173059	1	< 0.1%
3173056	1	< 0.1%
3172855	1	< 0.1%
3172830	1	< 0.1%
3172803	1	< 0.1%
3171951	1	< 0.1%
3171790	1	< 0.1%
3170723	1	< 0.1%
3169512	1	< 0.1%
3169510	1	< 0.1%

FechaInicioVigencia__ctrim
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	527.6 KiB

02-2021	6628
01-2021	1812

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	59080
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	01-2021
2nd row	01-2021
3rd row	01-2021
4th row	01-2021
5th row	01-2021

Common Values

Value	Count	Frequency (%)
02-2021	6628	78.5%
01-2021	1812	21.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
02-2021	6628	78.5%
01-2021	1812	21.5%

Most occurring characters

Value	Count	Frequency (%)
2	23508	39.8%
0	16880	28.6%
1	10252	17.4%
-	8440	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	50640	85.7%
Dash Punctuation	8440	14.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	23508	46.4%
0	16880	33.3%
1	10252	20.2%

Dash Punctuation

Value	Count	Frequency (%)
-	8440	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	59080	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	23508	39.8%
0	16880	28.6%
1	10252	17.4%
-	8440	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	59080	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	23508	39.8%
0	16880	28.6%
1	10252	17.4%
-	8440	14.3%

churn
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	478.2 KiB

1	4453
0	3987

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	8440
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

Most occurring characters

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	8440	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	8440	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8440	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	4453	52.8%
0	3987	47.2%

n_prod_prev
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.2%
Missing	6743
Missing (%)	79.9%
Memory size	363.0 KiB

2.0	1000
8.0	474
1.0	220
3.0	3

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	5091
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	8.0
2nd row	8.0
3rd row	1.0
4th row	2.0
5th row	8.0

Common Values

Value	Count	Frequency (%)
2.0	1000	11.8%
8.0	474	5.6%
1.0	220	2.6%
3.0	3	< 0.1%
(Missing)	6743	79.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
2.0	1000	58.9%
8.0	474	27.9%
1.0	220	13.0%
3.0	3	0.2%

Most occurring characters

Value	Count	Frequency (%)
.	1697	33.3%
0	1697	33.3%
2	1000	19.6%
8	474	9.3%
1	220	4.3%
3	3	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3394	66.7%
Other Punctuation	1697	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1697	50.0%
2	1000	29.5%
8	474	14.0%
1	220	6.5%
3	3	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	1697	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5091	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	1697	33.3%
0	1697	33.3%
2	1000	19.6%
8	474	9.3%
1	220	4.3%
3	3	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5091	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	1697	33.3%
0	1697	33.3%
2	1000	19.6%
8	474	9.3%
1	220	4.3%
3	3	0.1%

total_siniestros
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	21
Distinct (%)	1.1%
Missing	6581
Missing (%)	78.0%
Infinite	0
Infinite (%)	0.0%
Mean	89.05648198

Minimum	1
Maximum	150
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	38
median	150
Q3	150
95-th percentile	150
Maximum	150
Range	149
Interquartile range (IQR)	112

Descriptive statistics

Standard deviation	65.11927894
Coefficient of variation (CV)	0.7312132423
Kurtosis	-1.826563904
Mean	89.05648198
Median Absolute Deviation (MAD)	0
Skewness	-0.202468804
Sum	165556
Variance	4240.520489
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
150	974	11.5%
38	474	5.6%
1	227	2.7%
2	49	0.6%
3	41	0.5%
5	21	0.2%
4	15	0.2%
9	8	0.1%
7	8	0.1%
10	7	0.1%
Other values (11)	35	0.4%
(Missing)	6581	78.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	227	2.7%
2	49	0.6%
3	41	0.5%
4	15	0.2%
5	21	0.2%
6	4	< 0.1%
7	8	0.1%
8	5	0.1%
9	8	0.1%
10	7	0.1%

Value	Count	Frequency (%)
150	974	11.5%
80	1	< 0.1%
52	2	< 0.1%
38	474	5.6%
36	2	< 0.1%
28	2	< 0.1%
16	5	0.1%
14	5	0.1%
13	2	< 0.1%
12	4	< 0.1%

total_pagado_smmlv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	118
Distinct (%)	6.3%
Missing	6581
Missing (%)	78.0%
Infinite	0
Infinite (%)	0.0%
Mean	1478.300089

Minimum	0
Maximum	2414.537144
Zeros	194
Zeros (%)	2.3%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	816.7201723
median	2414.537144
Q3	2414.537144
95-th percentile	2414.537144
Maximum	2414.537144
Range	2414.537144
Interquartile range (IQR)	1597.816972

Descriptive statistics

Standard deviation	1020.381999
Coefficient of variation (CV)	0.6902400982
Kurtosis	-1.656355747
Mean	1478.300089
Median Absolute Deviation (MAD)	0
Skewness	-0.3116861175
Sum	2748159.865
Variance	1041179.423
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2414.537144	974	11.5%
816.7201723	474	5.6%
0	194	2.3%
27.2245838	10	0.1%
25.86077058	6	0.1%
21.9036109	6	0.1%
1.451869303	5	0.1%
190.333425	5	0.1%
19.7388624	5	0.1%
18.20160674	4	< 0.1%
Other values (108)	176	2.1%
(Missing)	6581	78.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	194	2.3%
0.07564339607	1	< 0.1%
0.1920019661	2	< 0.1%
0.245313584	1	< 0.1%
0.3200032768	3	< 0.1%
0.41883625	1	< 0.1%
0.430265105	1	< 0.1%
0.4327850326	2	< 0.1%
0.6666666667	1	< 0.1%
0.6830598665	1	< 0.1%

Value	Count	Frequency (%)
2414.537144	974	11.5%
877.1397546	2	< 0.1%
816.7201723	474	5.6%
433.9886806	1	< 0.1%
248.3894018	1	< 0.1%
226.2245633	4	< 0.1%
190.333425	5	0.1%
183.7270839	1	< 0.1%
175.9068007	2	< 0.1%
151.8519068	2	< 0.1%

anios_ultimo_siniestro
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	137
Distinct (%)	7.4%
Missing	6581
Missing (%)	78.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1627948448

Minimum	0.002739726027
Maximum	8.75890411
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0.002739726027
5-th percentile	0.002739726027
Q1	0.002739726027
median	0.002739726027
Q3	0.008219178082
95-th percentile	0.8
Maximum	8.75890411
Range	8.756164384
Interquartile range (IQR)	0.005479452055

Descriptive statistics

Standard deviation	0.7025660932
Coefficient of variation (CV)	4.315653202
Kurtosis	55.58336597
Mean	0.1627948448
Median Absolute Deviation (MAD)	0
Skewness	6.815919012
Sum	302.6356164
Variance	0.4935991153
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.002739726027	974	11.5%
0.008219178082	481	5.7%
0.07671232877	15	0.2%
0.07123287671	13	0.2%
0.04383561644	12	0.1%
0.06301369863	11	0.1%
0.01369863014	11	0.1%
0.8	11	0.1%
0.07397260274	10	0.1%
0.01095890411	9	0.1%
Other values (127)	312	3.7%
(Missing)	6581	78.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.002739726027	974	11.5%
0.005479452055	9	0.1%
0.008219178082	481	5.7%
0.01095890411	9	0.1%
0.01369863014	11	0.1%
0.01643835616	3	< 0.1%
0.02191780822	5	0.1%
0.02465753425	5	0.1%
0.02739726027	1	< 0.1%
0.0301369863	3	< 0.1%

Value	Count	Frequency (%)
8.75890411	1	< 0.1%
8	1	< 0.1%
7.178082192	3	< 0.1%
6.235616438	2	< 0.1%
6.008219178	1	< 0.1%
5.879452055	1	< 0.1%
5.090410959	3	< 0.1%
4.312328767	1	< 0.1%
4.17260274	1	< 0.1%
4.043835616	4	< 0.1%

Activos__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	1349
Distinct (%)	32.4%
Missing	4282
Missing (%)	50.7%
Infinite	0
Infinite (%)	0.0%
Mean	429678332.6

Minimum	0
Maximum	5.643561885 × 10¹⁰
Zeros	22
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0
5-th percentile	2000000
Q1	46000000.25
median	120000000
Q3	320000000
95-th percentile	1388556000
Maximum	5.643561885 × 10¹⁰
Range	5.643561885 × 10¹⁰
Interquartile range (IQR)	273999999.8

Descriptive statistics

Standard deviation	1757766913
Coefficient of variation (CV)	4.090890277
Kurtosis	356.5619219
Mean	429678332.6
Median Absolute Deviation (MAD)	99950000
Skewness	15.89519263
Sum	1.786602507 × 10¹²
Variance	3.089744521 × 10¹⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100000000	129	1.5%
50000000	118	1.4%
80000000	107	1.3%
150000000	101	1.2%
200000000	100	1.2%
300000000	89	1.1%
120000000	87	1.0%
60000000	86	1.0%
10000000	84	1.0%
1	78	0.9%
Other values (1339)	3179	37.7%
(Missing)	4282	50.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	22	0.3%
1	78	0.9%
2	37	0.4%
20	3	< 0.1%
10000	1	< 0.1%
107254	1	< 0.1%
127000	1	< 0.1%
200000	1	< 0.1%
500000	4	< 0.1%
600000	2	< 0.1%

Value	Count	Frequency (%)
5.643561885 × 10¹⁰	1	< 0.1%
3.2934155 × 10¹⁰	2	< 0.1%
2.8207083 × 10¹⁰	1	< 0.1%
2.379921321 × 10¹⁰	1	< 0.1%
1.9483034 × 10¹⁰	3	< 0.1%
1.7267744 × 10¹⁰	7	0.1%
1.56067031 × 10¹⁰	5	0.1%
1.1530782 × 10¹⁰	1	< 0.1%
1.024294018 × 10¹⁰	2	< 0.1%
7694534000	1	< 0.1%

AnnualRevenue
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	1454
Distinct (%)	35.0%
Missing	4282
Missing (%)	50.7%
Infinite	0
Infinite (%)	0.0%
Mean	320064858.7

Minimum	0
Maximum	4.24173603 × 10¹⁰
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0
5-th percentile	9039950
Q1	24000000
median	45736000
Q3	98000000
95-th percentile	777008000
Maximum	4.24173603 × 10¹⁰
Range	4.24173603 × 10¹⁰
Interquartile range (IQR)	74000000

Descriptive statistics

Standard deviation	2047397773
Coefficient of variation (CV)	6.396821511
Kurtosis	202.3120142
Mean	320064858.7
Median Absolute Deviation (MAD)	26264000
Skewness	13.33129356
Sum	1.330829682 × 10¹²
Variance	4.191837641 × 10¹⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
36000000	170	2.0%
24000000	139	1.6%
60000000	126	1.5%
30000000	125	1.5%
48000000	117	1.4%
12000000	91	1.1%
40000000	78	0.9%
50000000	68	0.8%
18000000	67	0.8%
42000000	52	0.6%
Other values (1444)	3125	37.0%
(Missing)	4282	50.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	8	0.1%
52230	1	< 0.1%
90790	1	< 0.1%
835000	1	< 0.1%
877000	1	< 0.1%
900000	1	< 0.1%
910000	1	< 0.1%
1000000	12	0.1%
1100000	4	< 0.1%

Value	Count	Frequency (%)
4.24173603 × 10¹⁰	2	< 0.1%
3.243391822 × 10¹⁰	1	< 0.1%
2.9375273 × 10¹⁰	7	0.1%
2.765797 × 10¹⁰	3	< 0.1%
1.897052621 × 10¹⁰	5	0.1%
1.7620986 × 10¹⁰	1	< 0.1%
1.742471143 × 10¹⁰	1	< 0.1%
1.4350938 × 10¹⁰	3	< 0.1%
1.2306478 × 10¹⁰	1	< 0.1%
1.0812427 × 10¹⁰	1	< 0.1%

MontoAnual__c
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	57.1%
Missing	8433
Missing (%)	99.9%
Memory size	330.0 KiB

0.0	4
102.0	1
3000.0	1
100.0	1

Length

Max length	6
Median length	3
Mean length	4
Min length	3

Characters and Unicode

Total characters	28
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	42.9%

Sample

1st row	102.0
2nd row	3000.0
3rd row	0.0
4th row	0.0
5th row	100.0

Common Values

Value	Count	Frequency (%)
0.0	4	< 0.1%
102.0	1	< 0.1%
3000.0	1	< 0.1%
100.0	1	< 0.1%
(Missing)	8433	99.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0.0	4	57.1%
102.0	1	14.3%
3000.0	1	14.3%
100.0	1	14.3%

Most occurring characters

Value	Count	Frequency (%)
0	17	60.7%
.	7	25.0%
1	2	7.1%
2	1	3.6%
3	1	3.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	21	75.0%
Other Punctuation	7	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	17	81.0%
1	2	9.5%
2	1	4.8%
3	1	4.8%

Other Punctuation

Value	Count	Frequency (%)
.	7	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	28	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	17	60.7%
.	7	25.0%
1	2	7.1%
2	1	3.6%
3	1	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	28	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	17	60.7%
.	7	25.0%
1	2	7.1%
2	1	3.6%
3	1	3.6%

OtrosIngresos__c
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
SKEWED
ZEROS

Distinct	105
Distinct (%)	3.1%
Missing	5105
Missing (%)	60.5%
Infinite	0
Infinite (%)	0.0%
Mean	2825766.49

Minimum	0
Maximum	3479487967
Zeros	3168
Zeros (%)	37.5%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0.6
Maximum	3479487967
Range	3479487967
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	62803920.5
Coefficient of variation (CV)	22.22544599
Kurtosis	2823.733557
Mean	2825766.49
Median Absolute Deviation (MAD)	0
Skewness	51.4657287
Sum	9423931245
Variance	3.944332431 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3168	37.5%
12000000	7	0.1%
20000000	7	0.1%
24000000	6	0.1%
5000000	6	0.1%
2000000	5	0.1%
6000000	5	0.1%
24199785	5	0.1%
15000000	4	< 0.1%
36000000	4	< 0.1%
Other values (95)	118	1.4%
(Missing)	5105	60.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	3168	37.5%
2	2	< 0.1%
4000	1	< 0.1%
9000	1	< 0.1%
37000	1	< 0.1%
227000	2	< 0.1%
274000	1	< 0.1%
529000	1	< 0.1%
529083	1	< 0.1%
577774	1	< 0.1%

Value	Count	Frequency (%)
3479487967	1	< 0.1%
655490000	1	< 0.1%
517969000	1	< 0.1%
196218120	1	< 0.1%
187969000	1	< 0.1%
165644000	2	< 0.1%
158400000	1	< 0.1%
144000000	1	< 0.1%
115280000	2	< 0.1%
109856000	1	< 0.1%

Profesion__pc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	8440
Missing (%)	100.0%
Memory size	66.1 KiB

EgresosAnuales__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	1096
Distinct (%)	26.4%
Missing	4282
Missing (%)	50.7%
Infinite	0
Infinite (%)	0.0%
Mean	271922356.5

Minimum	0
Maximum	4.033890964 × 10¹⁰
Zeros	2
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	0
5-th percentile	3485000
Q1	12680250
median	26255000
Q3	60000000
95-th percentile	600492469.5
Maximum	4.033890964 × 10¹⁰
Range	4.033890964 × 10¹⁰
Interquartile range (IQR)	47319750

Descriptive statistics

Standard deviation	1982687195
Coefficient of variation (CV)	7.291372512
Kurtosis	213.5733155
Mean	271922356.5
Median Absolute Deviation (MAD)	16255000
Skewness	13.83240589
Sum	1.130653158 × 10¹²
Variance	3.931048514 × 10¹⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12000000	183	2.2%
30000000	176	2.1%
18000000	156	1.8%
24000000	155	1.8%
20000000	134	1.6%
36000000	100	1.2%
40000000	100	1.2%
10000000	100	1.2%
15000000	90	1.1%
25000000	78	0.9%
Other values (1086)	2886	34.2%
(Missing)	4282	50.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	< 0.1%
1	25	0.3%
300000	1	< 0.1%
339561	1	< 0.1%
400000	2	< 0.1%
450000	7	0.1%
497395	1	< 0.1%
500000	9	0.1%
580000	1	< 0.1%
600000	5	0.1%

Value	Count	Frequency (%)
4.033890964 × 10¹⁰	2	< 0.1%
3.472297457 × 10¹⁰	1	< 0.1%
3.36 × 10¹⁰	1	< 0.1%
2.8430656 × 10¹⁰	7	0.1%
2.5171626 × 10¹⁰	3	< 0.1%
1.663542953 × 10¹⁰	1	< 0.1%
1.6135595 × 10¹⁰	1	< 0.1%
1.530540134 × 10¹⁰	5	0.1%
1.4149066 × 10¹⁰	3	< 0.1%
1.0675292 × 10¹⁰	1	< 0.1%

EstadoCivil__pc
Categorical

HIGH CORRELATION
MISSING

Distinct	8
Distinct (%)	0.2%
Missing	4141
Missing (%)	49.1%
Memory size	394.9 KiB

SOLTERO	2329
CASADO	1203
OTRO	689
UNIDO	49
VIUDO	12
Other values (3)	17

Length

Max length	10
Median length	7
Mean length	6.217027216
Min length	3

Characters and Unicode

Total characters	26727
Distinct characters	15
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	SOLTERO
2nd row	SOLTERO
3rd row	SOLTERO
4th row	CASADO
5th row	SOLTERO

Common Values

Value	Count	Frequency (%)
SOLTERO	2329	27.6%
CASADO	1203	14.3%
OTRO	689	8.2%
UNIDO	49	0.6%
VIUDO	12	0.1%
SEPARADO	9	0.1%
DIVORCIADO	7	0.1%
N A	1	< 0.1%
(Missing)	4141	49.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
soltero	2329	54.2%
casado	1203	28.0%
otro	689	16.0%
unido	49	1.1%
viudo	12	0.3%
separado	9	0.2%
divorciado	7	0.2%
n	1	< 0.1%
a	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
O	7323	27.4%
S	3541	13.2%
R	3034	11.4%
T	3018	11.3%
A	2432	9.1%
E	2338	8.7%
L	2329	8.7%
D	1287	4.8%
C	1210	4.5%
I	75	0.3%
Other values (5)	140	0.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	26726	> 99.9%
Space Separator	1	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
O	7323	27.4%
S	3541	13.2%
R	3034	11.4%
T	3018	11.3%
A	2432	9.1%
E	2338	8.7%
L	2329	8.7%
D	1287	4.8%
C	1210	4.5%
I	75	0.3%
Other values (4)	139	0.5%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	26726	> 99.9%
Common	1	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
O	7323	27.4%
S	3541	13.2%
R	3034	11.4%
T	3018	11.3%
A	2432	9.1%
E	2338	8.7%
L	2329	8.7%
D	1287	4.8%
C	1210	4.5%
I	75	0.3%
Other values (4)	139	0.5%

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	26727	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
O	7323	27.4%
S	3541	13.2%
R	3034	11.4%
T	3018	11.3%
A	2432	9.1%
E	2338	8.7%
L	2329	8.7%
D	1287	4.8%
C	1210	4.5%
I	75	0.3%
Other values (5)	140	0.5%

Genero__pc
Categorical

HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	0.1%
Missing	4141
Missing (%)	49.1%
Memory size	405.5 KiB

MASCULINO	3122
FEMENINO	1176
N A	1

Length

Max length	9
Median length	9
Mean length	8.725052338
Min length	3

Characters and Unicode

Total characters	37509
Distinct characters	12
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	MASCULINO
2nd row	FEMENINO
3rd row	MASCULINO
4th row	FEMENINO
5th row	MASCULINO

Common Values

Value	Count	Frequency (%)
MASCULINO	3122	37.0%
FEMENINO	1176	13.9%
N A	1	< 0.1%
(Missing)	4141	49.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
masculino	3122	72.6%
femenino	1176	27.3%
n	1	< 0.1%
a	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
N	5475	14.6%
M	4298	11.5%
I	4298	11.5%
O	4298	11.5%
A	3123	8.3%
S	3122	8.3%
C	3122	8.3%
U	3122	8.3%
L	3122	8.3%
E	2352	6.3%
Other values (2)	1177	3.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	37508	> 99.9%
Space Separator	1	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	5475	14.6%
M	4298	11.5%
I	4298	11.5%
O	4298	11.5%
A	3123	8.3%
S	3122	8.3%
C	3122	8.3%
U	3122	8.3%
L	3122	8.3%
E	2352	6.3%

Space Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	37508	> 99.9%
Common	1	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	5475	14.6%
M	4298	11.5%
I	4298	11.5%
O	4298	11.5%
A	3123	8.3%
S	3122	8.3%
C	3122	8.3%
U	3122	8.3%
L	3122	8.3%
E	2352	6.3%

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	37509	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	5475	14.6%
M	4298	11.5%
I	4298	11.5%
O	4298	11.5%
A	3123	8.3%
S	3122	8.3%
C	3122	8.3%
U	3122	8.3%
L	3122	8.3%
E	2352	6.3%
Other values (2)	1177	3.1%

ciudad_name
Categorical

HIGH CORRELATION
MISSING

Distinct	22
Distinct (%)	0.5%
Missing	4141
Missing (%)	49.1%
Memory size	397.0 KiB

otras	3769
BOGOTÁ D.C.	185
MEDELLIN	80
CALI	39
PASTO	26
Other values (17)	200

Length

Max length	13
Median length	5
Mean length	5.478250756
Min length	4

Characters and Unicode

Total characters	23551
Distinct characters	31
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.1%

Sample

1st row	otras
2nd row	otras
3rd row	otras
4th row	otras
5th row	otras

Common Values

Value	Count	Frequency (%)
otras	3769	44.7%
BOGOTÁ D.C.	185	2.2%
MEDELLIN	80	0.9%
CALI	39	0.5%
PASTO	26	0.3%
BUCARAMANGA	25	0.3%
ARMENIA	25	0.3%
MANIZALES	24	0.3%
CÚCUTA	23	0.3%
BARRANQUILLA	19	0.2%
Other values (12)	84	1.0%
(Missing)	4141	49.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
otras	3769	83.8%
bogotá	185	4.1%
d.c	185	4.1%
medellin	80	1.8%
cali	39	0.9%
pasto	26	0.6%
bucaramanga	25	0.6%
armenia	25	0.6%
manizales	24	0.5%
cúcuta	23	0.5%
Other values (17)	119	2.6%

Most occurring characters

Value	Count	Frequency (%)
o	3769	16.0%
r	3769	16.0%
a	3769	16.0%
s	3769	16.0%
t	3769	16.0%
A	457	1.9%
O	433	1.8%
.	370	1.6%
C	341	1.4%
L	300	1.3%
Other values (21)	2805	11.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	18845	80.0%
Uppercase Letter	4135	17.6%
Other Punctuation	370	1.6%
Space Separator	201	0.9%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	457	11.1%
O	433	10.5%
C	341	8.2%
L	300	7.3%
E	294	7.1%
D	281	6.8%
I	278	6.7%
T	248	6.0%
B	232	5.6%
N	230	5.6%
Other values (14)	1041	25.2%

Lowercase Letter

Value	Count	Frequency (%)
o	3769	20.0%
r	3769	20.0%
a	3769	20.0%
s	3769	20.0%
t	3769	20.0%

Other Punctuation

Value	Count	Frequency (%)
.	370	100.0%

Space Separator

Value	Count	Frequency (%)
	201	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	22980	97.6%
Common	571	2.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	3769	16.4%
r	3769	16.4%
a	3769	16.4%
s	3769	16.4%
t	3769	16.4%
A	457	2.0%
O	433	1.9%
C	341	1.5%
L	300	1.3%
E	294	1.3%
Other values (19)	2310	10.1%

Common

Value	Count	Frequency (%)
.	370	64.8%
	201	35.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	23332	99.1%
None	219	0.9%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	3769	16.2%
r	3769	16.2%
a	3769	16.2%
s	3769	16.2%
t	3769	16.2%
A	457	2.0%
O	433	1.9%
.	370	1.6%
C	341	1.5%
L	300	1.3%
Other values (18)	2586	11.1%

None

Value	Count	Frequency (%)
Á	194	88.6%
Ú	23	10.5%
É	2	0.9%

edad
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	3487
Distinct (%)	81.1%
Missing	4142
Missing (%)	49.1%
Infinite	0
Infinite (%)	0.0%
Mean	46.44473186

Minimum	1.578082192
Maximum	122.5041096
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	66.1 KiB

Quantile statistics

Minimum	1.578082192
5-th percentile	26.20808219
Q1	35.35410959
median	45.00273973
Q3	56.35410959
95-th percentile	70.82684932
Maximum	122.5041096
Range	120.9260274
Interquartile range (IQR)	21

Descriptive statistics

Standard deviation	14.21402064
Coefficient of variation (CV)	0.3060416126
Kurtosis	0.1622937524
Mean	46.44473186
Median Absolute Deviation (MAD)	10.44931507
Skewness	0.4328453742
Sum	199619.4575
Variance	202.0383827
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
52.80273973	8	0.1%
58.14520548	7	0.1%
73.04383562	7	0.1%
51.91506849	6	0.1%
64.90958904	6	0.1%
35.57808219	5	0.1%
61.60273973	5	0.1%
48.04657534	5	0.1%
42.45205479	5	0.1%
76.28767123	5	0.1%
Other values (3477)	4239	50.2%
(Missing)	4142	49.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.578082192	1	< 0.1%
2.402739726	1	< 0.1%
5.61369863	1	< 0.1%
6.356164384	1	< 0.1%
7.580821918	2	< 0.1%
7.846575342	2	< 0.1%
8.638356164	1	< 0.1%
8.98630137	1	< 0.1%
9.920547945	1	< 0.1%
10.95616438	1	< 0.1%

Value	Count	Frequency (%)
122.5041096	3	< 0.1%
112.7917808	1	< 0.1%
103.0657534	1	< 0.1%
89.6109589	1	< 0.1%
88.8630137	1	< 0.1%
88.48493151	1	< 0.1%
87.54246575	1	< 0.1%
87.44383562	2	< 0.1%
86.5260274	1	< 0.1%
85.86575342	1	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	CodigoTipoAsegurado__c	PuntoVenta__c	tipo_ramo_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	TipoVehiculo__c	NumeroPoliza__c	FechaInicioVigencia__ctrim	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro	Activos__c	AnnualRevenue	MontoAnual__c	OtrosIngresos__c	Profesion__pc	EgresosAnuales__c	EstadoCivil__pc	Genero__pc	ciudad_name	edad
0	1	1203	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1009923	01-2021	0	NaN	NaN	NaN	NaN	500000000.0	300000000.0	NaN	NaN	NaN	250000000.0	SOLTERO	MASCULINO	otras	34.846575
1	1	1002	automoviles	automoviles	99999	NaN	NaN	99999	3048712	01-2021	0	8.0	38.0	816.720172	0.008219	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	1	1002	automoviles	automoviles	99999	NaN	NaN	99999	3052432	01-2021	0	8.0	38.0	816.720172	0.008219	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	1	8042	automoviles	automoviles	99999	NaN	NaN	99999	3075559	01-2021	1	NaN	NaN	NaN	NaN	80000000.0	40000000.0	NaN	0.0	NaN	14000000.0	SOLTERO	FEMENINO	otras	40.619178
4	4	1048	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	3001185	01-2021	0	NaN	1.0	0.000000	1.087671	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5	1	604	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1010150	01-2021	0	NaN	NaN	NaN	NaN	77000000.0	40000000.0	NaN	0.0	NaN	27000000.0	SOLTERO	MASCULINO	otras	62.473973
6	1	3202	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1058558	01-2021	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
7	2	404	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1002013	01-2021	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8	4	404	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1001169	01-2021	0	NaN	2.0	0.000000	1.452055	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
9	1	1048	responsabilidad civil	profesionales medicos	99999	NaN	NaN	99999	1004260	01-2021	1	NaN	1.0	4.971463	0.136986	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Last rows

	CodigoTipoAsegurado__c	PuntoVenta__c	tipo_ramo_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	TipoVehiculo__c	NumeroPoliza__c	FechaInicioVigencia__ctrim	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro	Activos__c	AnnualRevenue	MontoAnual__c	OtrosIngresos__c	Profesion__pc	EgresosAnuales__c	EstadoCivil__pc	Genero__pc	ciudad_name	edad
8430	1	5	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1000060	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8431	1	9477	automoviles	automoviles	99999	NaN	NaN	99999	3051776	02-2021	0	8.0	38.0	816.720172	0.008219	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8432	1	9721	automoviles	automoviles	99999	NaN	NaN	99999	3173056	02-2021	1	2.0	150.0	2414.537144	0.002740	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8433	1	604	automoviles	automoviles	99999	NaN	NaN	99999	3007792	02-2021	1	NaN	NaN	NaN	NaN	100000000.0	53000000.0	NaN	0.0	NaN	47000000.0	UNIDO	MASCULINO	otras	37.139726
8434	1	1701	automoviles	automoviles	99999	NaN	NaN	99999	3000238	02-2021	1	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8435	1	8001	responsabilidad civil	profesionales medicos	99999	NaN	NaN	99999	1004215	02-2021	1	NaN	16.0	190.333425	0.060274	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8436	1	3301	automoviles	automoviles	99999	NaN	NaN	99999	3075773	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8437	1	8001	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1027255	02-2021	1	NaN	NaN	NaN	NaN	600000000.0	100000000.0	NaN	0.0	NaN	70000000.0	SOLTERO	MASCULINO	BOGOTÁ D.C.	51.517808
8438	1	8001	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1027331	02-2021	0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8439	1	8001	responsabilidad civil	extracontractual	99999	NaN	NaN	99999	1027428	02-2021	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts